REMOTE HEALTH ASSERTION VERIFICATION AND HEALTH PREDICTION SYSTEM

• US 20190180852A1
• Filed: 02/19/2019
• Published: 06/13/2019
• Est. Priority Date: 11/14/2014
• Status: Active Grant

• Current Assignee: Dasir LLC
• Original Assignee: Health Equity Labs
• Inventors: Jiao, Shuo, Shah, Munjal, Hinchey, Ryan, Fan, Cathy Ye, Singh, Ardaman
• Granted Patent: US 10,930,378 B2
• Time in Patent Office: Days
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A computing system can implement a health verification and prediction service by generating an interactive user interface through which users can provide responses to health assertions in one or more trivia sessions. Each of the health assertions can include a correlation value to actual health outcomes based on responses received from individuals a control group and the known health outcomes of those individuals. Based on the responses from the user, the computing system can generate a health profile for the user.

Claims

1. A computing system implementing a health prediction service, comprising:

a network communication interface to communicate, over one or more networks, with computing devices of users of the health prediction service;

a database storing a library of health assertions, each health assertion in the library being associated with a correlation value based on answers to the health assertion from individuals in a control group of which a health outcome is known;

one or more processors; and

a memory resource storing instructions that, when executed by the one or more processors, cause the computing system to;

generate, over the one or more networks, an interactive user interface for display on a computing device of a user of the health prediction service, the interactive user interface presenting a sequence health assertions from the library of health assertions, wherein for each health assertion in the sequence, the user is prompted to select from a plurality of possible responses, and wherein a single response from the plurality of possible responses to each health assertion in the sequence comprises a correct response;

receive, over the one or more networks, a corresponding sequence of responses to the sequence of health assertions, each response in the corresponding sequence comprising either the correct response or an incorrect response;

generate an individualized user interface element for the user on the interactive user interface, the individualized user interface element comprising a health knowledge score based at least in part on the corresponding sequence of responses and a set of and a classification of the user as compared to other users of the health prediction service; and

based at least in part on the health knowledge score of the user, generate a health profile for the user.

2. The computing system of claim 1, wherein the executed instructions further cause the computing system to:

receive, over the one or more networks, selection data indicating a set of self-classifications made by the user from the computing device of the user.

3. The computing system of claim 2, wherein the set of self-classifications identify one or more health classifications of the user.

4. The computing system of claim 2, wherein the executed instructions further cause the computing system to:

using the health knowledge score of the user, verify the set of self-classifications made by the user.

5. The computing system of claim 4, wherein the executed instructions cause the computing system to further generate the health profile of the user based on verifying the set of self-classifications.

6. The computing system of claim 1, wherein the executed instructions further cause the computing system to:

based on health data from the control group and the answers to each health assertion provided by the individuals of the control group, generate a mortality table for the health prediction service, the mortality table being predictive of a person'"'"'s probability of death over a given timeframe based at least in part on health knowledge.

7. The computing system of claim 6, wherein the executed instructions cause the computing system to generate the health profile of the user by determining a position of the user in the mortality table.

8. The computing system of claim 1, wherein the executed instructions cause the computing system to generate the health profile of the user by determining one or more health risks of the user.

9. The computing system of claim 1, wherein health profile is utilized by the computing system to automatically generate a price structure for a health product.

10. The computing system of claim 9, wherein the health product comprises one of a health insurance product or a life insurance product.

11. The computing system of claim 1, wherein the executed instructions further cause the computing system to:

receive health outcome data indicating actual health outcomes of a subset of the users of the health prediction service;

based on the health outcome data, (i) incorporate the subset of users into the control group, and (ii) update the correlation value of one or more health assertions in the library of health assertions.

12. The computing system of claim 11, wherein the correlation value correlates knowledge of each respective health assertion in the library of health assertions to a health outcome prediction.

13. A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:

communicate, over one or more networks, with computing devices of users of a health prediction service;

store a library of health assertions in a database, each health assertion in the library being associated with a correlation value based on answers to the health assertion from individuals in a control group of which a health outcome is known;

generate, over the one or more networks, an interactive user interface for display on a computing device of a user of the health prediction service, the interactive user interface presenting a sequence health assertions from the library of health assertions, wherein for each health assertion in the sequence, the user is prompted to select from a plurality of possible responses, and wherein a single response from the plurality of possible responses to each health assertion in the sequence comprises a correct response;

receive, over the one or more networks, a corresponding sequence of responses to the sequence of health assertions, each response in the corresponding sequence comprising either the correct response or an incorrect response;

generate an individualized user interface element for the user on the interactive user interface, the individualized user interface element comprising a health knowledge score based at least in part on the corresponding sequence of responses and a set of and a classification of the user as compared to other users of the health prediction service; and

based at least in part on the health knowledge score of the user, generate a health profile for the user.

14. The non-transitory computer readable medium of claim 13, wherein the executed instructions further cause the one or more processors to:

receive, over the one or more networks, selection data indicating a set of self-classifications made by the user from the computing device of the user.

15. The non-transitory computer readable medium of claim 14, wherein the set of self-classifications identify one or more health classifications of the user.

16. The non-transitory computer readable medium of claim 14, wherein the executed instructions further cause the one or more processors to:

using the health knowledge score of the user, verify the set of self-classifications made by the user.

17. The non-transitory computer readable medium of claim 16, wherein the executed instructions cause the one or more processors to further generate the health profile of the user based on verifying the set of self-classifications.

18. The non-transitory computer readable medium of claim 13, wherein the executed instructions further cause the one or more processors to:

based on health data from the control group and the answers to each health assertion provided by the individuals of the control group, generate a mortality table for the health prediction service, the mortality table being predictive of a person'"'"'s probability of death over a given timeframe based at least in part on health knowledge.

19. The non-transitory computer readable medium of claim 18, wherein the executed instructions cause the one or more processors to generate the health profile of the user by determining a position of the user in the mortality table.

20. A computer-implemented method of implementing a health prediction service, the method being performed by one or more processors and comprising:

communicating, over one or more networks, with computing devices of users of a health prediction service;

storing a library of health assertions in a database, each health assertion in the library being associated with a correlation value based on answers to the health assertion from individuals in a control group of which a health outcome is known;

generating, over the one or more networks, an interactive user interface for display on a computing device of a user of the health prediction service, the interactive user interface presenting a sequence health assertions from the library of health assertions, wherein for each health assertion in the sequence, the user is prompted to select from a plurality of possible responses, and wherein a single response from the plurality of possible responses to each health assertion in the sequence comprises a correct response;

receiving, over the one or more networks, a corresponding sequence of responses to the sequence of health assertions, each response in the corresponding sequence comprising either the correct response or an incorrect response;

generating an individualized user interface element for the user on the interactive user interface, the individualized user interface element comprising a health knowledge score based at least in part on the corresponding sequence of responses and a set of and a classification of the user as compared to other users of the health prediction service; and

based at least in part on the health knowledge score of the user, generating a health profile for the user.